Easy whole-brain modeling for computational neuroscientists 🧠💻👩🏿🔬
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Updated
May 13, 2024 - Python
Easy whole-brain modeling for computational neuroscientists 🧠💻👩🏿🔬
Python library to compute different properties of quantum tight binding models in a lattice
Python library to compute different properties of tight binding models
Package to perform tight binding calculation in tight binding models, with a friendly user interface
User-friendly open-source software to design and solve tight-binding models, addressing electronic properties, topology, interactions, non-collinear magnetism, and unconventional superconductivity, among others.
paper lists and information on mean-field theory of deep learning
Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
Implementation of deep implicit attention in PyTorch
Hartree-Fock-Bogoliubov solver for a generic interacting fermion Hamiltonian
Computational statistical mechanics of field-responsive polymer chains
Automatic Differentiation Mean Field Approach
Implementation of Variational Mean Field Inference for dense Conditional Random Fields.
Package for solving generalized BdG mean field theory of interacting systems.
Mean field theory and cavity method implementation.
Numerical integration of mean-field equations for large-scale leaky integrate-and-fire neuronal network simulations incorporating synaptic plasticity via Graupner Brunel model. Includes support for a memory-induction stim-pop.
A C++ program for solving the mean field equation in Holstein model and periodic Anderson model with Holstein phonons, with phonon displacement as the order parameter.
A collection of programs and scripts to solve and analyze the Kane-Mele-Hubbard model in a variety of (dynamical) mean-field settings
Mean field methods in the context of continuum mechanics with special focus on orientation averaging homogenization
description coming soon
Physics-inspired transformer modules based on mean-field dynamics of vector-spin models in JAX
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